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alexandros-kyriakides/TestingJupyter.ipynb

Last active May 4, 2018 09:29
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TestingJupyter.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"a=np.random.randn(5,10)\n",
"df=pd.DataFrame(a)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([[ 0.25667056, -0.54613993, -0.53358287, 1.6901468 , 1.71452835,\n",
" 1.06650029, 0.42516294, 0.01132299, -0.8453335 , -0.1417125 ],\n",
" [ 0.26840916, 0.63369548, 1.58034111, -2.68132071, -0.34309488,\n",
" 1.17044296, -1.37417243, 2.03242369, -1.23752365, -0.81402051],\n",
" [ 1.67947016, -0.81944661, -2.36651522, 0.24932272, -0.39210187,\n",
" -0.24161567, -0.21745463, 0.20701174, 0.03480106, -1.25807151],\n",
" [-1.57912305, -0.58028377, -1.74454584, -0.61049945, 0.53314022,\n",
" 1.51806752, 0.66769863, -0.25394667, -0.67776064, -0.9001706 ],\n",
" [ 1.51912649, -0.93449435, -2.01671768, 0.41377538, -1.80908068,\n",
" -0.76608966, -2.35199004, -0.27889756, -0.32385296, -1.20976817]])"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" <th>5</th>\n",
" <th>6</th>\n",
" <th>7</th>\n",
" <th>8</th>\n",
" <th>9</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 0.256671</td>\n",
" <td>-0.546140</td>\n",
" <td>-0.533583</td>\n",
" <td> 1.690147</td>\n",
" <td> 1.714528</td>\n",
" <td> 1.066500</td>\n",
" <td> 0.425163</td>\n",
" <td> 0.011323</td>\n",
" <td>-0.845334</td>\n",
" <td>-0.141712</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 0.268409</td>\n",
" <td> 0.633695</td>\n",
" <td> 1.580341</td>\n",
" <td>-2.681321</td>\n",
" <td>-0.343095</td>\n",
" <td> 1.170443</td>\n",
" <td>-1.374172</td>\n",
" <td> 2.032424</td>\n",
" <td>-1.237524</td>\n",
" <td>-0.814021</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 1.679470</td>\n",
" <td>-0.819447</td>\n",
" <td>-2.366515</td>\n",
" <td> 0.249323</td>\n",
" <td>-0.392102</td>\n",
" <td>-0.241616</td>\n",
" <td>-0.217455</td>\n",
" <td> 0.207012</td>\n",
" <td> 0.034801</td>\n",
" <td>-1.258072</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-1.579123</td>\n",
" <td>-0.580284</td>\n",
" <td>-1.744546</td>\n",
" <td>-0.610499</td>\n",
" <td> 0.533140</td>\n",
" <td> 1.518068</td>\n",
" <td> 0.667699</td>\n",
" <td>-0.253947</td>\n",
" <td>-0.677761</td>\n",
" <td>-0.900171</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> 1.519126</td>\n",
" <td>-0.934494</td>\n",
" <td>-2.016718</td>\n",
" <td> 0.413775</td>\n",
" <td>-1.809081</td>\n",
" <td>-0.766090</td>\n",
" <td>-2.351990</td>\n",
" <td>-0.278898</td>\n",
" <td>-0.323853</td>\n",
" <td>-1.209768</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3 4 5 6 \\\n",
"0 0.256671 -0.546140 -0.533583 1.690147 1.714528 1.066500 0.425163 \n",
"1 0.268409 0.633695 1.580341 -2.681321 -0.343095 1.170443 -1.374172 \n",
"2 1.679470 -0.819447 -2.366515 0.249323 -0.392102 -0.241616 -0.217455 \n",
"3 -1.579123 -0.580284 -1.744546 -0.610499 0.533140 1.518068 0.667699 \n",
"4 1.519126 -0.934494 -2.016718 0.413775 -1.809081 -0.766090 -2.351990 \n",
"\n",
" 7 8 9 \n",
"0 0.011323 -0.845334 -0.141712 \n",
"1 2.032424 -1.237524 -0.814021 \n",
"2 0.207012 0.034801 -1.258072 \n",
"3 -0.253947 -0.677761 -0.900171 \n",
"4 -0.278898 -0.323853 -1.209768 \n",
"\n",
"[5 rows x 10 columns]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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